Physical Limitations To Nonuniformity Correction In IR Focal Plane Arrays

Scribner, Dean A.; Kruer, M.; Gridley, J C; Sarkady, Kenneth A.

doi:10.1117/12.943565

Cited by 26 publications

(17 citation statements)

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“…The LMS error function is exploited for the calibration and the method of Steepest Descent optimizes the gain and offset correction coefficients slowly [12], [9]:…”

Section: Shutter-based Calibrationmentioning

confidence: 99%

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An innovative real time system for infrared focal plan array image enhancement based on FPGA

Koohestani

Homaei

2008

Real-Time Image Processing 2008

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The conceptual configuration and special features of a new high-precision real-time signal processing system for a Cooled Infrared Focal Plan Array with 320×240 detectors is presented in this note. The most critical case in the image detectors based on array elements is the Non-Uniformity Correction (NUC) between the sensitive elements due to the different characteristics of the materials in fabrication phase, especially for the IRFPAs with high elements which their non-uniformities are inherently more severe. It is the case that a mechanism for NUC between the sensitive elements needs a structure for compensation of gradual drift in the detectors' output by update the correction factors in a regular way. A feasible method, Least-Mean-Square under a compact hardware is introduced. The correction formula deduced from this approach is the best approximation polynomial of the analytic formula through theoretical analysis. Inherently, the intended detector has not a suitable timing for sending out for standard display equipments, so it is essential to have hardware for frame-to-frame grab which can help for processing applications too. Applying a capability of the sophisticated FPGAs, the contrast enhancement based on Bi-Histogram Equalization which preserves the brightness of infrared image precisely is described.

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“…The LMS error function is exploited for the calibration and the method of Steepest Descent optimizes the gain and offset correction coefficients slowly [12], [9]:…”

Section: Shutter-based Calibrationmentioning

confidence: 99%

“…Thanks to developments of semiconductor techniques, implementation of some complicated algorithms in real-time schemes becomes possible [5], [7], [8], [9], [10], [11]. This paper describes some new techniques in FPGA for realization image enhancement system.…”

Section: Introductionmentioning

confidence: 99%

An innovative real time system for infrared focal plan array image enhancement based on FPGA

Koohestani

Homaei

2008

Real-Time Image Processing 2008

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“…It is possible to compensate for nonuniformity using a linear correction if the gain and bias coefficients of the linear model are known for each detector. But complicating matters, the nonuniformity tends to drift over time, changing over a nominal time period of minutes or hours [4][5] . This precludes a simple one-time factory nonuniformity correction (NUC) from completely eradicating the problem.…”

Section: Introductionmentioning

confidence: 99%

“…Variability in the production of infrared focal plane arrays (IR FPAs) causes individual detectors within an FPA to respond differently to the same level of irradiance [1][2][3][4][5] . This nonuniformity limits imaging performance because it interferes with the spatial information of the true scene.…”

Section: Introductionmentioning

confidence: 99%

Scene-based nonuniformity correction using texture-based adaptive filtering

Droege

2007

SPIE Proceedings

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The detectors within an infrared focal plane array (FPA) characteristically have responses that vary from detector to detector. It is desirable to remove this "nonuniformity" for improved image quality. Factory calibration is not sufficient since nonuniformity tends to drift over time. Field calibration can be performed using uniform temperature sources but requires briefly obscuring the field-of-view and leads to additional system size and cost. Alternative "scene-based" approaches are able to utilize the normal scene data when performing non-uniformity correction (NUC) and therefore do not require the field-of-view to be obscured. These function well under proper conditions but at times can introduce image artifacts such as "ghosting". Ghosting results when scene conditions are not optimal for NUC. The scene-based approach presented in this paper estimates a correction term for each detector using spatial information. In parallel, motion estimation and texture features are used to identify frames and regions within frames that are suitable for NUC. This information is then employed to adaptively converge to the proper correction terms for each detector in the FPA.

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“…Nonuniformity correction is a key problem that must be first solved in IRFPA systems. The detector-to-detector responsivity (gain) and dark current (offset) variations [3][4][5][6][7], which cause the nonuniformity, may completely mask the useful thermal signatures in an IR image with a fixed pattern ''noise''. In order to get better resolution, a 12 or 14 bit ADC is commonly adopted in the signal processing system [2].…”

Section: Introductionmentioning

confidence: 99%